V0508HMA15HPHI3B1 / README.md
L0I6T1Z9Y
upload V0508HMA15HPHI3B1
8a6c937
|
raw
history blame
3.11 kB
metadata
license: mit
base_model: microsoft/Phi-3-mini-4k-instruct
tags:
  - generated_from_trainer
model-index:
  - name: V0508HMA15HPHI3B1
    results: []

V0508HMA15HPHI3B1

This model is a fine-tuned version of microsoft/Phi-3-mini-4k-instruct on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0759

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.0003
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine_with_restarts
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 3
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
4.0539 0.09 10 0.4056
0.2678 0.18 20 0.2377
0.3002 0.27 30 0.2459
0.2402 0.36 40 0.2783
0.2519 0.45 50 0.2303
0.2249 0.54 60 0.2132
0.2258 0.63 70 0.2016
0.21 0.73 80 0.1504
0.1338 0.82 90 0.1060
0.1138 0.91 100 0.0950
0.0903 1.0 110 0.0831
0.0717 1.09 120 0.0837
0.0936 1.18 130 0.1182
0.1048 1.27 140 0.0978
0.0863 1.36 150 0.0781
0.0892 1.45 160 0.0815
0.0731 1.54 170 0.0752
0.0702 1.63 180 0.0796
0.0714 1.72 190 0.0733
0.0709 1.81 200 0.0745
0.065 1.9 210 0.0868
0.0647 1.99 220 0.0789
0.0361 2.08 230 0.0826
0.0325 2.18 240 0.0823
0.0264 2.27 250 0.0894
0.0284 2.36 260 0.0787
0.0343 2.45 270 0.0776
0.0258 2.54 280 0.0808
0.0274 2.63 290 0.0791
0.0315 2.72 300 0.0775
0.0315 2.81 310 0.0768
0.0232 2.9 320 0.0760
0.0297 2.99 330 0.0759

Framework versions

  • Transformers 4.36.0.dev0
  • Pytorch 2.1.2+cu121
  • Datasets 2.18.0
  • Tokenizers 0.14.1